As is their custom, Cloudera Engineering’s interns made innovation, especially for Apache Spark, the theme of the Summer season.
Cloudera has a long-time tradition of searching far and wide for the smartest summer engineering interns that it can find. Alumni of the program have become start-up co-founders, faculty at top-tier CS departments, employees at other prominent technology companies (including Google, Databricks, Uber, LinkedIn), as well as many current employees at Cloudera.
We’re pleased to announce the release of Cloudera Enterprise 5.4 (comprising CDH 5.4, Cloudera Manager 5.4, and Cloudera Navigator 2.3).
Cloudera Enterprise 5.4 (Release Notes) reflects critical investments in a production-ready customer experience through governance, security, performance and deployment flexibility in cloud environments. It also includes support for a significant number of updated open standard components–including Apache Spark 1.3, Impala 2.2, and Apache HBase 1.0 (as well as unsupported beta releases of Hive-on-Spark data processing and OpenStack deployments).
Following these best practices can make your upgrade path to CDH 5 relatively free of obstacles.
Upgrading the software that powers mission-critical workloads can be challenging in any circumstance. In the case of CDH, however, Cloudera Manager makes upgrades easy, and the built-in Upgrade Wizard, available with Cloudera Manager 5, further simplifies the upgrade process. The wizard performs service-specific upgrade steps that, previously, you had to run manually, and also features a rolling restart capability that reduces downtime for minor and maintenance version upgrades.
Set up your own, or even a shared, environment for doing interactive analysis of time-series data.
Although software engineering offers several methods and approaches to produce robust and reliable components, a more lightweight and flexible approach is required for data analysts—who do not build “products” per se but still need high-quality tools and components. Thus, recently, I tried to find a way to re-use existing libraries and datasets stored already in HDFS with Apache Spark.
A Hive-on-Spark beta is now available via CDH parcel. Give it a try!
The Hive-on-Spark project (HIVE-7292) is one of the most watched projects in Apache Hive history. It has attracted developers from across the ecosystem, including from organizations such as Intel, MapR, IBM, and Cloudera, and gained critical help from the Spark community.
Many anxious users have inquired about its availability in the last few months.